摘要
数据可视化对于从海量数据中发现规律、增强数据表现、提升交互效率具有重要作用。目前,数据可视化的概念及相关研究领域不断扩展,就数据类型而言,可视化研究逐渐聚焦于多维数据、时序数据、网络数据和层次化数据等领域。通过对中国知网(CNKI)中外文文献进行分析可知:2014年、2015年是数据可视化领域研究热度升级、理论成果大量产出的"里程碑"式年份;中国大数据领域研究热潮形成后,数据可视化是迅速发展的一个重要支撑领域;国内外数据可视化领域的研究,在时间上基本同步,而武汉大学、浙江大学、北京邮电大学、国防科技大学、电子科技大学等都是在该领域研究活跃度较高的国内高校。要获得良好的视觉效果,帮助用户降低理解难度,高效分析数据和洞悉价值,通常还需要注意色彩与语义、突出核心数据、防止数据过载、防止思维过度发散等技术要点。现有的数据可视化技术主要分为基于几何技术、基于图标技术、基于降维技术、面向像素技术、基于时间序列技术、基于网络数据技术的数据可视化方法,以及层次可视化技术和分布技术等。基于几何技术的可视化方法,包括平行坐标、散点图矩阵、Andrews曲线等。基于坐标的可视化方法,可以清晰展示变量间的关系,但受限于屏幕尺寸,当数据维度超过3个时,难以直观显示全部维度,需要结合人机交互技术进行展示,适用于表达不同维度之间的相关关系,比如学生学习行为之间的关联关系等。基于图标的可视化方法,主要包括星绘法和Chernoff面法,以几何图形作为图标刻画多维数据,直观反映出图标各个维度所表示的意义,适用于工作完成情况、激励工作进度概览等。基于降维技术的可视化方法,根据维度属性确定点的坐标,在保持数据关系不变的前提下映射到低维可视空间中,主要涉及主成分�
Data visualization plays an important role in discovering rules from massive data, enhancing data performance and improving interaction efficiency.At present, the concept of data visualization and related research fields are expanding.In terms of data types, the current visualization research gradually focuses on the fields of multidimensional data, time series data, network data and hierarchical data.Through the analysis of Chinese and foreign literature on CNKI,it can be seen that 2014 and 2015 are "milestone" years in which the research heat in the field of data visualization is upgraded and a large number of theoretical achievements are produced;Data visualization is an important supporting field of rapid development after the formation of the research upsurge in the field of big data in China;The research in the field of data visualization at home and abroad has basically achieved synchronization in time;Wuhan University, Zhejiang University, Beijing University of Posts and telecommunications, University of national defense science and technology and University of Electronic Science and technology research actively in this field in China.In order to obtain good visual effects, help users reduce the difficulty of understanding, efficiently analyze data and insight value, It is usually necessary to pay attention to technical points such as color and semantics, highlighting core data, preventing data overload and preventing excessive divergence of thinking.The existing data visualization technologies are mainly divided into geometry based technology, icon based technology, dimension reduction based technology, pixel oriented technology, time series based technology, network data based technology, hierarchical visualization technology and distribution technology.Visualization methods based on geometric technology, including parallel coordinates, scatter matrix, Andrews curve, etc;The coordinate based visualization method can clearly show the relationship between variables, but limited by the screen size, it is d
作者
刘滨
刘增杰
刘宇
李子文
陈莉
孙中贤
王莹
张一辉
赵佳盛
张红斌
刘青
LIU Bin;LIU Zengjie;LIU Yu;LI Ziwen;CHEN Li;SUN Zhongxian;WANG Ying;ZHANG Yihui;ZHAO Jiasheng;ZHANG Hongbin;LIU Qing(School of Economics and Management,Hebei University of Science and Technology,Shijiazhuang,Hebei 050018,China;Research Center of Big Data and Social Computing,Hebei University of Science and Technology,Shijiazhuang,Hebei 050018,China;Library,Hebei Professional College of Political Science and Law,Shijiazhuang,Hebei 050061,China;Hebei Institute of Laser Company Limited,Shijiazhuang,Hebei 050081,China;Air Force Early Warning Academy,Wuhan,Hubei 430019,China;School of Information Science and Engineering,Hebei University of Science and Techno-logy,Shijiazhuang,Hebei 050018,China)
出处
《河北科技大学学报》
CAS
北大核心
2021年第6期643-654,共12页
Journal of Hebei University of Science and Technology
基金
国家文化和旅游科技创新工程项目(2020年度)
河北省省级科技计划资助项目(20310802D,21310101D,20310701D)
河北省社会科学基金项目(HB20TQ008)
河北省高层次人才资助项目(A2016002015)
河北省创新能力提升计划项目(20551801K)
石家庄市科学技术研究与发展计划项目(19SCX01006,191130591A)。
关键词
计算机图形学
数据可视化
多维数据
时序数据
网络数据
层次化数据
computer graphics
data visualization
multidimensional data
time series data
network data
hierarchical data
